{"total":78,"rows":[{"id":"2411.06070","title":"GFT: Graph Foundation Model with Transferable Tree Vocabulary","created":"2024-11-09","cited_by_count":85,"area":null},{"id":"2406.12031","title":"Large Scale Transfer Learning for Tabular Data via Language Modeling","created":"2024-06-17","cited_by_count":76,"area":null},{"id":"2405.08011","title":"A Survey of Large Language Models for Graphs","created":"2024-05-10","cited_by_count":72,"area":null},{"id":"2502.05424","title":"SAMGPT: Text-free Graph Foundation Model for Multi-domain Pre-training and Cross-domain Adaptation","created":"2025-02-08","cited_by_count":62,"area":null},{"id":"2408.14512","title":"LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token Embeddings","created":"2024-08-25","cited_by_count":61,"area":null},{"id":"2407.09709","title":"GOFA: A Generative One-For-All Model for Joint Graph Language Modeling","created":"2024-07-12","cited_by_count":57,"area":null},{"id":"2409.09957","title":"Deep Graph Anomaly Detection: A Survey and New Perspectives","created":"2024-09-16","cited_by_count":40,"area":null},{"id":"2502.01113","title":"GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation","created":"2025-02-03","cited_by_count":40,"area":"rag"},{"id":"2502.03251","title":"RiemannGFM: Learning a Graph Foundation Model from Riemannian Geometry","created":"2025-02-05","cited_by_count":35,"area":null},{"id":"2508.20906","title":"Turning Tabular Foundation Models into Graph Foundation Models","created":"2025-08-28","cited_by_count":35,"area":null},{"id":"2404.14928","title":"Graph Machine Learning in the Era of Large Language Models (LLMs)","created":"2024-04-23","cited_by_count":33,"area":null},{"id":"2412.16441","title":"Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees","created":"2024-12-21","cited_by_count":32,"area":null},{"id":"2408.12025","title":"Exploring Large Language Models for Feature Selection: A Data-centric Perspective","created":"2024-08-21","cited_by_count":27,"area":null},{"id":"2407.11095","title":"DeepGate3: Towards Scalable Circuit Representation Learning","created":"2024-07-15","cited_by_count":26,"area":null},{"id":"2503.03313","title":"LLM as GNN: Graph Vocabulary Learning for Text-Attributed Graph Foundation Models","created":"2025-03-05","cited_by_count":22,"area":null},{"id":"2509.21489","title":"GraphPFN: A Prior-Data Fitted Graph Foundation Model","created":"2025-09-25","cited_by_count":21,"area":null},{"id":"2409.14500","title":"GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data","created":"2024-09-22","cited_by_count":20,"area":null},{"id":"2406.12052","title":"UniGLM: Training One Unified Language Model for Text-Attributed Graph Embedding","created":"2024-06-17","cited_by_count":14,"area":null},{"id":"2505.12684","title":"Towards Effective Federated Graph Foundation Model via Mitigating Knowledge Entanglement","created":"2025-05-19","cited_by_count":14,"area":null},{"id":"2501.01124","title":"Graph2text or Graph2token: A Perspective of Large Language Models for Graph Learning","created":"2025-01-02","cited_by_count":12,"area":null},{"id":"2410.19084","title":"GCoder: Improving Large Language Model for Generalized Graph Problem Solving","created":"2024-10-24","cited_by_count":11,"area":"lr"},{"id":"2602.13697","title":"No Need to Train Your RDB Foundation Model","created":"2026-02-14","cited_by_count":10,"area":null},{"id":"2403.16137","title":"A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective","created":"2024-03-24","cited_by_count":9,"area":null},{"id":"2510.07755","title":"FedBook: A Unified Federated Graph Foundation Codebook with Intra-domain and Inter-domain Knowledge Modeling","created":"2025-10-09","cited_by_count":8,"area":null},{"id":"2503.09363","title":"Towards Graph Foundation Models: A Transferability Perspective","created":"2025-03-12","cited_by_count":7,"area":null},{"id":"2504.10917","title":"Towards A Universal Graph Structural Encoder","created":"2025-04-15","cited_by_count":7,"area":null},{"id":"2507.16541","title":"A Comprehensive Data-centric Overview of Federated Graph Learning","created":"2025-07-22","cited_by_count":7,"area":null},{"id":"2510.16885","title":"UniGTE: Unified Graph-Text Encoding for Zero-Shot Generalization across Graph Tasks and Domains","created":"2025-10-19","cited_by_count":7,"area":null},{"id":"2602.04116","title":"Toward Effective Multimodal Graph Foundation Model: A Divide-and-Conquer Based Approach","created":"2026-02-04","cited_by_count":7,"area":null},{"id":"2404.03354","title":"A Comprehensive Survey on Self-Supervised Learning for Recommendation","created":"2024-04-04","cited_by_count":6,"area":null},{"id":"2410.12609","title":"Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs","created":"2024-10-16","cited_by_count":6,"area":null},{"id":"2407.11025","title":"Backdoor Graph Condensation","created":"2024-07-03","cited_by_count":5,"area":null},{"id":"2603.00618","title":"Multi-Domain Riemannian Graph Gluing for Building Graph Foundation Models","created":"2026-02-28","cited_by_count":5,"area":null},{"id":"2412.07407","title":"Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings","created":"2024-12-10","cited_by_count":4,"area":null},{"id":"2606.24509","title":"A Fair Evaluation of Graph Foundation Models for Node Property Prediction","created":"2026-06-23","cited_by_count":4,"area":null},{"id":"2407.15320","title":"Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligence","created":"2024-07-07","cited_by_count":3,"area":null},{"id":"2412.19211","title":"Large Language Models Meet Graph Neural Networks: A Perspective of Graph Mining","created":"2024-12-26","cited_by_count":3,"area":null},{"id":"2503.10722","title":"TacticExpert: Spatial-Temporal Graph Language Model for Basketball Tactics","created":"2025-03-13","cited_by_count":3,"area":null},{"id":"2506.02044","title":"A Brain Graph Foundation Model: Pre-Training and Prompt-Tuning across Broad Atlases and Disorders","created":"2025-05-31","cited_by_count":3,"area":null},{"id":"2506.22510","title":"Towards Text-free Graph Foundation Models: Rethinking Multi-Domain Graph Contrastive Learning","created":"2025-06-26","cited_by_count":3,"area":null},{"id":"2511.17982","title":"Towards Effective, Stealthy, and Persistent Backdoor Attacks Targeting Graph Foundation Models","created":"2025-11-22","cited_by_count":3,"area":"safety"},{"id":"2605.04834","title":"Bridging Input Feature Spaces Towards Graph Foundation Models","created":"2026-05-06","cited_by_count":3,"area":null},{"id":"2406.10426","title":"MiNT: Multi-Network Training for Transfer Learning on Temporal Graphs","created":"2024-06-14","cited_by_count":2,"area":null},{"id":"2409.02035","title":"A Modern Take on Visual Relationship Reasoning for Grasp Planning","created":"2024-09-03","cited_by_count":2,"area":null},{"id":"2503.11086","title":"A Survey of Cross-domain Graph Learning: Progress and Future Directions","created":"2025-03-14","cited_by_count":2,"area":null},{"id":"2506.14098","title":"Toward a Graph Foundation Model: Pre-Training Transformers With Random Walks","created":"2025-06-17","cited_by_count":2,"area":null},{"id":"2509.21097","title":"GraphUniverse: Synthetic Graph Generation for Evaluating Inductive Generalization","created":"2025-09-25","cited_by_count":2,"area":null},{"id":"2510.04567","title":"GILT: An LLM-Free, Tuning-Free Graph Foundational Model for In-Context Learning","created":"2025-10-06","cited_by_count":2,"area":null},{"id":"2601.11954","title":"Data-centric Prompt Tuning for Dynamic Graphs","created":"2026-01-17","cited_by_count":2,"area":null},{"id":"2603.18797","title":"VesselTok: Tokenizing Vessel-like 3D Biomedical Graph Representations for Reconstruction and Generation","created":"2026-03-19","cited_by_count":2,"area":null},{"id":"2505.12027","title":"Relation-Aware Graph Foundation Model","created":"2025-05-17","cited_by_count":1,"area":null},{"id":"2602.11052","title":"GraphSeek: Next-Generation Graph Analytics with LLMs","created":"2026-02-11","cited_by_count":1,"area":null},{"id":"2602.18709","title":"IRIS-SLAM: Unified Geo-Instance Representations for Robust Semantic Localization and Mapping","created":"2026-02-21","cited_by_count":1,"area":null},{"id":"2603.13799","title":"Node Role-Guided LLMs for Dynamic Graph Clustering","created":"2026-03-14","cited_by_count":1,"area":null},{"id":"2603.21601","title":"Riemannian Geometry Speaks Louder Than Words: From Graph Foundation Model to Next-Generation Graph Intelligence","created":"2026-03-23","cited_by_count":1,"area":null},{"id":"2605.14809","title":"GFMate: Empowering Graph Foundation Models with Test-time Prompt Tuning","created":"2026-05-14","cited_by_count":1,"area":null},{"id":"2606.22462","title":"Adaptive Recurrent Message Passing for Test Time Computing on Graphs","created":"2026-06-21","cited_by_count":1,"area":null},{"id":"2407.19941","title":"Boosting Graph Foundation Model from Structural Perspective","created":"2024-07-29","cited_by_count":0,"area":null},{"id":"2502.00282","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","created":"2025-02-01","cited_by_count":0,"area":null},{"id":"2503.00476","title":"G-OSR: A Comprehensive Benchmark for Graph Open-Set Recognition","created":"2025-03-01","cited_by_count":0,"area":null},{"id":"2505.03799","title":"Scalability Matters: Overcoming Challenges in InstructGLM with Similarity-Degree-Based Sampling","created":"2025-05-02","cited_by_count":0,"area":null},{"id":"2509.08401","title":"Two Facets of the Same Optimization Coin: Model Degradation and Representation Collapse in Graph Foundation Models","created":"2025-09-10","cited_by_count":0,"area":null},{"id":"2601.21067","title":"Out-of-Distribution Generalization in Graph Foundation Models","created":"2026-01-28","cited_by_count":0,"area":null},{"id":"2603.06618","title":"Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networks","created":"2026-02-20","cited_by_count":0,"area":"distill"},{"id":"2604.22031","title":"Mochi: Aligning Pre-training and Inference for Efficient Graph Foundation Models via Meta-Learning","created":"2026-04-23","cited_by_count":0,"area":null},{"id":"2606.03270","title":"Are Common Substructures Transferable? Riemannian Graph Foundation Model with Neural Vector Bundles","created":"2026-06-02","cited_by_count":0,"area":null},{"id":"2606.11898","title":"GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMs","created":"2026-06-10","cited_by_count":0,"area":null},{"id":"2607.18567","title":"Attacking Graph Foundation Models Through Their Shared Representation","created":"2026-07-20","cited_by_count":0,"area":null},{"id":"2607.19108","title":"OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation","created":"2026-07-21","cited_by_count":0,"area":null},{"id":"2607.26533","title":"AgentGFM: A Graph Foundation Model with Node-Agent Information-Flow Control","created":"2026-07-29","cited_by_count":0,"area":"agents"},{"id":"2608.08567","title":"Neural Message Passing on Structural Interaction Graphs for Fully-Inductive Graph Neural Networks","created":"2026-08-09","cited_by_count":0,"area":null},{"id":"2609.18107","title":"FoundAna: A GNN-assisted Foundation Model for Graph Anomaly Detection","created":"2026-09-16","cited_by_count":0,"area":null},{"id":"2609.25722","title":"Signed Graph Pre-Training and Prompt Learning","created":"2026-09-22","cited_by_count":0,"area":null},{"id":"2609.30894","title":"Training Graph Foundation Models on The Web Graph","created":"2026-09-25","cited_by_count":0,"area":null},{"id":"2609.37604","title":"GraphVQ: Structure-Aware Autoregressive Decoding over Context-Quantized Graph Tokens","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.02881","title":"Toward Omni Multimodal Graph Foundation Model: A Topology-Driven Binding Approach","created":"2026-10-02","cited_by_count":0,"area":null},{"id":"2610.14710","title":"DeKoR: Decomposed Knowledge Routing for Efficient GNN--LLM Fusion","created":"2026-10-10","cited_by_count":0,"area":null},{"id":"2610.15427","title":"Riemannian Graph Tokenizer for Structural Knowledge Transfer","created":"2026-10-11","cited_by_count":0,"area":null}],"next_cursor":null}